{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2> 6. Bayes Classification </h2>\n",
    "\n",
    "This notebook has the code for the charts in Chapter 6\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Install BigQuery module\n",
    "\n",
    "You don't need this on AI Platform, but you need this on plain-old JupyterLab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install google-cloud-bigquery"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext google.cloud.bigquery"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "PROJECT = 'data-science-on-gcp-180606' # REPLACE WITH YOUR PROJECT ID\n",
    "BUCKET = 'data-science-on-gcp' # REPLACE WITH YOUR BUCKET NAME\n",
    "REGION = 'us-central1' # REPLACE WITH YOUR BUCKET REGION e.g. us-central1\n",
    "\n",
    "os.environ['BUCKET'] = BUCKET"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3> Exploration using BigQuery </h3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import google.cloud.bigquery as bigquery\n",
    "\n",
    "bq = bigquery.Client()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sql = \"\"\"\n",
    "SELECT DISTANCE, DEP_DELAY\n",
    "FROM `flights.tzcorr`\n",
    "WHERE RAND() < 0.001 AND dep_delay > -20 AND dep_delay < 30 AND distance < 2000\n",
    "\"\"\"\n",
    "df = bq.query(sql).to_dataframe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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c2RjERMZAIPBafhK71zkGVdiSzzFR3XQuKYBUsnbyAUFZbXU7l/I/q3IQQFSW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\n3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fTZ/tMoBdNjma5nDtWDpmo/6O9sWTpl9XTaOwijY+0O3XKdTpjpvgXDsHvGTORZHEvj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\nIiJq8P8BYqwrsSGRpqsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6e9c21ba10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"whitegrid\")\n",
    "g = sns.jointplot(df['DISTANCE'], df['DEP_DELAY'], kind=\"hex\", size=10, joint_kws={'gridsize':20})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3> Set up views in Spark SQL </h3>\n",
    "\n",
    "Start a Spark Session if necessary and get a handle to it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<pyspark.sql.session.SparkSession object at 0x7f6e9c2088d0>\n"
     ]
    }
   ],
   "source": [
    "from pyspark.sql import SparkSession\n",
    "spark = SparkSession \\\n",
    "    .builder \\\n",
    "    .appName(\"Bayes classification using Spark\") \\\n",
    "    .getOrCreate()\n",
    "print(spark)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set up the schema to read in the CSV files on GCS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "StructType(List(StructField(FL_DATE,StringType,true),StructField(UNIQUE_CARRIER,StringType,true),StructField(AIRLINE_ID,StringType,true),StructField(CARRIER,StringType,true),StructField(FL_NUM,StringType,true),StructField(ORIGIN_AIRPORT_ID,StringType,true),StructField(ORIGIN_AIRPORT_SEQ_ID,StringType,true),StructField(ORIGIN_CITY_MARKET_ID,StringType,true),StructField(ORIGIN,StringType,true),StructField(DEST_AIRPORT_ID,StringType,true),StructField(DEST_AIRPORT_SEQ_ID,StringType,true),StructField(DEST_CITY_MARKET_ID,StringType,true),StructField(DEST,StringType,true),StructField(CRS_DEP_TIME,StringType,true),StructField(DEP_TIME,StringType,true),StructField(DEP_DELAY,FloatType,true),StructField(TAXI_OUT,StringType,true),StructField(WHEELS_OFF,StringType,true),StructField(WHEELS_ON,StringType,true),StructField(TAXI_IN,StringType,true),StructField(CRS_ARR_TIME,StringType,true),StructField(ARR_TIME,StringType,true),StructField(ARR_DELAY,FloatType,true),StructField(CANCELLED,StringType,true),StructField(CANCELLATION_CODE,StringType,true),StructField(DIVERTED,StringType,true),StructField(DISTANCE,FloatType,true),StructField(DEP_AIRPORT_LAT,StringType,true),StructField(DEP_AIRPORT_LON,StringType,true),StructField(DEP_AIRPORT_TZOFFSET,StringType,true),StructField(ARR_AIRPORT_LAT,StringType,true),StructField(ARR_AIRPORT_LON,StringType,true),StructField(ARR_AIRPORT_TZOFFSET,StringType,true),StructField(EVENT,StringType,true),StructField(NOTIFY_TIME,StringType,true)))\n"
     ]
    }
   ],
   "source": [
    "from pyspark.sql.types import StringType, FloatType, StructType, StructField\n",
    "\n",
    "header = 'FL_DATE,UNIQUE_CARRIER,AIRLINE_ID,CARRIER,FL_NUM,ORIGIN_AIRPORT_ID,ORIGIN_AIRPORT_SEQ_ID,ORIGIN_CITY_MARKET_ID,ORIGIN,DEST_AIRPORT_ID,DEST_AIRPORT_SEQ_ID,DEST_CITY_MARKET_ID,DEST,CRS_DEP_TIME,DEP_TIME,DEP_DELAY,TAXI_OUT,WHEELS_OFF,WHEELS_ON,TAXI_IN,CRS_ARR_TIME,ARR_TIME,ARR_DELAY,CANCELLED,CANCELLATION_CODE,DIVERTED,DISTANCE,DEP_AIRPORT_LAT,DEP_AIRPORT_LON,DEP_AIRPORT_TZOFFSET,ARR_AIRPORT_LAT,ARR_AIRPORT_LON,ARR_AIRPORT_TZOFFSET,EVENT,NOTIFY_TIME'\n",
    "\n",
    "def get_structfield(colname):\n",
    "   if colname in ['ARR_DELAY', 'DEP_DELAY', 'DISTANCE']:\n",
    "      return StructField(colname, FloatType(), True)\n",
    "   else:\n",
    "      return StructField(colname, StringType(), True)\n",
    "\n",
    "schema = StructType([get_structfield(colname) for colname in header.split(',')])\n",
    "print(schema)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a table definition (this is done lazily; the files won't be read until we issue a query):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "inputs = 'gs://{}/flights/tzcorr/all_flights-00000-*'.format(BUCKET) # 1/30th\n",
    "#inputs = 'gs://{}/flights/tzcorr/all_flights-*'.format(BUCKET)  # FULL\n",
    "flights = spark.read\\\n",
    "            .schema(schema)\\\n",
    "            .csv(inputs)\n",
    "\n",
    "# this view can now be queried ...\n",
    "flights.createOrReplaceTempView('flights')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Example query over the view (this will take a while; it's Spark SQL, not BigQuery):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------+\n",
      "|count(1)|\n",
      "+--------+\n",
      "|    8813|\n",
      "+--------+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "results = spark.sql('SELECT COUNT(*) FROM flights WHERE dep_delay > -20 AND distance < 2000')\n",
    "results.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2> Restrict to train days </h2>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's create a CSV file of the training days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "sql = \"\"\"\n",
    "SELECT *\n",
    "FROM `flights.trainday`\n",
    "\"\"\"\n",
    "df = bq.query(sql).to_dataframe()\n",
    "df.to_csv('trainday.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FL_DATE,is_train_day\n",
      "2015-01-01,True\n",
      "2015-01-04,True\n"
     ]
    }
   ],
   "source": [
    "!head -3 trainday.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Copying file://trainday.csv [Content-Type=text/csv]...\n",
      "/ [1 files][  6.3 KiB/  6.3 KiB]                                                \n",
      "Operation completed over 1 objects/6.3 KiB.                                      \n"
     ]
    }
   ],
   "source": [
    "%%bash\n",
    "gcloud storage cp trainday.csv gs://${BUCKET}/flights/trainday.csv"   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create dataframe of traindays, but this time because the file has a header, and is a small file, we can have Spark infer the schema"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "traindays = spark.read \\\n",
    "    .option(\"header\", \"true\") \\\n",
    "    .option(\"inferSchema\", \"true\") \\\n",
    "    .csv('gs://{}/flights/trainday.csv'.format(BUCKET))\n",
    "\n",
    "traindays.createOrReplaceTempView('traindays')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Row(FL_DATE=datetime.datetime(2015, 1, 1, 0, 0), is_train_day=True),\n",
       " Row(FL_DATE=datetime.datetime(2015, 1, 4, 0, 0), is_train_day=True),\n",
       " Row(FL_DATE=datetime.datetime(2015, 1, 5, 0, 0), is_train_day=True),\n",
       " Row(FL_DATE=datetime.datetime(2015, 1, 7, 0, 0), is_train_day=True),\n",
       " Row(FL_DATE=datetime.datetime(2015, 1, 8, 0, 0), is_train_day=True)]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results = spark.sql('SELECT * FROM traindays')\n",
    "results.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "statement = \"\"\"\n",
    "SELECT\n",
    "  f.FL_DATE AS date,\n",
    "  distance,\n",
    "  dep_delay\n",
    "FROM flights f\n",
    "JOIN traindays t\n",
    "ON f.FL_DATE == t.FL_DATE\n",
    "WHERE\n",
    "  t.is_train_day AND\n",
    "  f.dep_delay IS NOT NULL\n",
    "ORDER BY\n",
    "  f.dep_delay DESC\n",
    "\"\"\"\n",
    "flights = spark.sql(statement)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3> Hexbin plot </h3>\n",
    "\n",
    "Create a hexbin plot using Spark (repeat of what we did in BigQuery, except that we are now restricting to train days only)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-------+----------+-----------------+-------------------+\n",
      "|summary|      date|         distance|          dep_delay|\n",
      "+-------+----------+-----------------+-------------------+\n",
      "|  count|      8311|             8311|               8311|\n",
      "|   mean|      null|748.7310792925039|-1.4972927445554085|\n",
      "| stddev|      null|441.1737503226965|  7.327984777613346|\n",
      "|    min|2015-11-26|             31.0|              -19.0|\n",
      "|    max|2015-11-27|           1999.0|               29.0|\n",
      "+-------+----------+-----------------+-------------------+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df = flights[(flights['distance'] < 2000) & (flights['dep_delay'] > -20) & (flights['dep_delay'] < 30)]\n",
    "df.describe().show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sample the dataframe so that it fits into memory (not a problem in development, but will be on full dataset); then plot it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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tVtOOHTsWZhid9u/fr9NOO02nnXaann32We3evVuvf/3r9e///u+65JJLlE6n9dOf/lSf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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6e97a59f10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pdf = df.sample(False, 0.02, 20).toPandas()  # to 100,000 rows approx on complete dataset\n",
    "g = sns.jointplot(pdf['distance'], pdf['dep_delay'], kind=\"hex\", size=10, joint_kws={'gridsize':20})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3> Quantization </h3>\n",
    "\n",
    "Now find the quantiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[31.0, 301.0, 369.0, 452.0, 588.0, 719.0, 925.0, 1067.0, 1235.0, 1750.0]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "distthresh = flights.approxQuantile('distance', list(np.arange(0, 1.0, 0.1)), 0.02)\n",
    "distthresh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[-31.0, -8.0, -6.0, -5.0, -4.0, -3.0, -2.0, -1.0, 2.0, 22.0]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "delaythresh = flights.approxQuantile('dep_delay', list(np.arange(0, 1.0, 0.1)), 0.05)\n",
    "delaythresh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+--------+\n",
      "|count(1)|\n",
      "+--------+\n",
      "|      62|\n",
      "+--------+\n",
      "\n"
     ]
    }
   ],
   "source": [
    "results = spark.sql('SELECT COUNT(*) FROM flights WHERE dep_delay >= 3 AND dep_delay < 8 AND distance >= 447 AND distance < 557')\n",
    "results.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2> Repeat, but on full dataset </h2>\n",
    "\n",
    "You can launch the above processing on the full dataset from within JupyterLab if you want the statistics and graphs updated. I didn't, though, because this is not what I would have really done. Instead, \n",
    "I would have created a standalone Python script and submitted it to the cluster -- there is no need to put JupyterLab in the middle of a production process. We'll submit a standalone Pig program to the cluster in the next section.\n",
    "\n",
    "Steps:\n",
    "<ol>\n",
    "<li> Change the input variable to process all-flights-* </li>\n",
    "<li> Increase cluster size (bash increase_cluster.sh from CloudShell) </li>\n",
    "<li> Clear all cells from this notebook </li>\n",
    "<li> Run all cells </li>\n",
    "<li> Decrease cluster size (bash decrease_cluster.sh from CloudShell) </li>\n",
    "</ol>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Copyright 2019 Google Inc. Licensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License."
   ]
  }
 ],
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